| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import torch | |
| # Load Qwen model | |
| model_name = "Qwen/Qwen-7B" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained(model_name) | |
| def chat(prompt): | |
| inputs = tokenizer(prompt, return_tensors="pt") | |
| outputs = model.generate(**inputs, max_length=100) | |
| return tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| # Example | |
| prompt = "Hello, how are you?" | |
| print(chat(prompt)) |